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Next-generation sequencing-based clinical sequencing: toward precision medicine in solid tumors

  • Toshifumi Wakai
  • Pankaj Prasoon
  • Yuki Hirose
  • Yoshifumi Shimada
  • Hiroshi Ichikawa
  • Masayuki Nagahashi
Invited Review Article
  • 65 Downloads

Abstract

Numerous technical and functional advances in next-generation sequencing (NGS) have led to the adoption of this technique in conventional clinical practice. Recently, large-scale genomic research and NGS technological innovation have revealed many more details of somatic and germline mutations in solid tumors. This development is allowing for the classification of tumor type sub-categories based on genetic alterations in solid tumors, and based on this information, new drugs and targeted therapies are being administered to patients. This has largely been facilitated by gene panel testing, which allows for a better understanding of the genetic basis for an individual’s response to therapy. NGS-based comprehensive gene panel testing is a clinically useful approach to investigate genomic mechanisms, including therapy-related signaling pathways, microsatellite instability, hypermutated phenotypes, and tumor mutation burden. In this review, we describe the concept of precision medicine in solid tumors using NGS-based comprehensive gene panel testing, as well as the importance of quality control of tissue sample handling in routine NGS-based genomic testing, and we discuss issues for the future adoption of this technique in Japan.

Keywords

Next-generation sequencing Precision medicine Solid tumors Genomic panel test Hypermutation Tumor mutation burden 

Notes

Compliance with ethical standards

Conflict of interest

Toshifumi Wakai received remuneration from Denka Company Limited and received research funding from Denka Company Limited, Eisai Co., Ltd.; Taisho Toyama Pharmaceutical Co., Ltd.; Taiho Pharmaceutical Co., Ltd.; Sumitomo Dainippon Pharma Co., Ltd.; Takeda Pharmaceutical Co., Ltd.; Chugai Pharmaceutical Co., Ltd.; Eli Lilly Japan K.K.; and Yakult Honsha Co., Ltd. Pankaj Prasoon, Yuki Hirose, Yoshifumi Shimada, Hiroshi Ichikawa, and Masayuki Nagahashi have no conflict of interest to disclose.

References

  1. 1.
    Reuter JA, Spacek DV, Snyder MP (2015) High-throughput sequencing technologies. Mol Cell 58:586–597CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Gerlinger M, Rowan AJ, Horswell S et al (2012) Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 366:883–892CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Shyr D, Liu Q (2013) Next generation sequencing in cancer research and clinical application. Biol Proced Online 15:4CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Akbani R, Ng PK, Werner HM et al (2014) A pan-cancer proteomic perspective on The Cancer Genome Atlas. Nat Commun 5:3887CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Robson ME, Bradbury AR, Arun B et al (2015) American Society of Clinical Oncology Policy Statement Update: Genetic and Genomic Testing for Cancer Susceptibility. J Clin Oncol 33:3660–3667CrossRefPubMedGoogle Scholar
  6. 6.
    Stanislaw C, Xue Y, Wilcox WR (2016) Genetic evaluation and testing for hereditary forms of cancer in the era of next-generation sequencing. Cancer Biol Med 13:55–67CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Pleasance ED, Cheetham RK, Stephens PJ et al (2010) A comprehensive catalogue of somatic mutations from a human cancer genome. Nature 463:191–196CrossRefPubMedGoogle Scholar
  8. 8.
    Weinstein JN, Collisson EA, Mills GB et al (2013) The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45:1113–1120CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Futreal PA, Coin L, Marshall M et al (2004) A census of human cancer genes. Nat Rev Cancer 4:177–183CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Forbes SA, Beare D, Gunasekaran P et al (2015) COSMIC: exploring the world’s knowledge of somatic mutations in human cancer. Nucleic Acids Res 43:D805–D811CrossRefPubMedGoogle Scholar
  11. 11.
    Vogelstein B, Papadopoulos N, Velculescu VE et al (2013) Cancer genome landscapes. Science 339:1546–1558CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Stratton MR, Campbell PJ, Futreal PA (2009) The cancer genome. Nature 458:719–724CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Ellis MJ, Perou CM (2013) The genomic landscape of breast cancer as a therapeutic roadmap. Cancer Discov 3:27–34CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Clinical Lung Cancer Genome Project (CLCGP); Network Genomic Medicine (NGM) (2013) A genomics-based classification of human lung tumors. Sci Transl Med 5:209ra153CrossRefGoogle Scholar
  15. 15.
    Wu K, Huang RS, House L et al (2013) Next-generation sequencing for lung cancer. Future Oncol 9:1323–1336CrossRefPubMedGoogle Scholar
  16. 16.
    Lianos GD, Mangano A, Cho WC et al (2015) From standard to new genome-based therapy of gastric cancer. Expert Rev Gastroenterol Hepatol 9:1023–1026CrossRefPubMedGoogle Scholar
  17. 17.
    Nagahashi M, Shimada Y, Ichikawa H et al (2018) Next generation sequencing-based gene panel tests for the management of solid tumor. Cancer Sci.  https://doi.org/10.1111/cas.13837 CrossRefPubMedGoogle Scholar
  18. 18.
    Varmus H (2003) Genomic empowerment: the importance of public databases. Nat Genet 35(Suppl 1):3CrossRefPubMedGoogle Scholar
  19. 19.
    Varmus H, Stillman B (2005) Support for the Human Cancer Genome Project. Science 310:1615CrossRefPubMedGoogle Scholar
  20. 20.
    Wheeler DA, Wang L (2013) From human genome to cancer genome: the first decade. Genome Res 23:1054–1062CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Endrullat C, Glokler J, Franke P et al (2016) Standardization and quality management in next-generation sequencing. Appl Transl Genom 10:2–9CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Nagahashi M, Shimada Y, Ichikawa H et al (2017) Formalin-fixed paraffin-embedded sample conditions for deep next generation sequencing. J Surg Res 220:125–132CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Arreaza G, Qiu P, Pang L et al (2016) Pre-analytical considerations for successful next-generation Sequencing (NGS): challenges and opportunities for formalin-fixed and paraffin-embedded tumor tissue (FFPE) samples. Int J Mol Sci 17(9):1579CrossRefPubMedCentralGoogle Scholar
  24. 24.
    Stephens PJ, Greenman CD, Fu B et al (2011) Massive genomic rearrangement acquired in a single catastrophic event during cancer development. Cell 144:27–40CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Baca SC, Prandi D, Lawrence MS et al (2013) Punctuated evolution of prostate cancer genomes. Cell 153:666–677CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Kandoth C, McLellan MD, Vandin F et al (2013) Mutational landscape and significance across 12 major cancer types. Nature 502:333–339CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Le Tourneau C, Delord JP, Goncalves A et al (2015) Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer (SHIVA): a multicentre, open-label, proof-of-concept, randomised, controlled phase 2 trial. Lancet Oncol 16:1324–1334CrossRefPubMedGoogle Scholar
  28. 28.
    Xue Y, Ankala A, Wilcox WR et al (2015) Solving the molecular diagnostic testing conundrum for Mendelian disorders in the era of next-generation sequencing: single-gene, gene panel, or exome/genome sequencing. Genet Med 17:444–451CrossRefPubMedGoogle Scholar
  29. 29.
    Horak P, Fröhling S, Glimm H (2016) Integrating next-generation sequencing into clinical oncology: strategies, promises and pitfalls. ESMO Open 1(5):e000094CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Garraway LA, Lander ES (2013) Lessons from the cancer genome. Cell 153:17–37CrossRefPubMedGoogle Scholar
  31. 31.
    Hodi FS, O’Day SJ, McDermott DF et al (2010) Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med 363:711–723CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Brahmer J, Reckamp KL, Baas P et al (2015) Nivolumab versus docetaxel in advanced squamous-cell non-small-cell lung cancer. N Engl J Med 373:123–135CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Yuza K, Nagahashi M, Watanabe S et al (2017) Hypermutation and microsatellite instability in gastrointestinal cancers. Oncotarget 8:112103–112115CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Cancer Genome Atlas Network (2012) Comprehensive molecular characterization of human colon and rectal cancer. Nature 487:330–337CrossRefGoogle Scholar
  35. 35.
    Nagahashi M, Wakai T, Shimada Y et al (2016) Genomic landscape of colorectal cancer in Japan: clinical implications of comprehensive genomic sequencing for precision medicine. Genome Med 8:136CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Mensenkamp AR, Vogelaar IP, van Zelst-Stams WA et al (2014) Somatic mutations in MLH1 and MSH2 are a frequent cause of mismatch-repair deficiency in Lynch syndrome-like tumors. Gastroenterology 146:643–646.e648CrossRefGoogle Scholar
  37. 37.
    Kautto EA, Bonneville R, Miya J et al (2017) Performance evaluation for rapid detection of pan-cancer microsatellite instability with MANTIS. Oncotarget 8:7452–7463CrossRefGoogle Scholar
  38. 38.
    Hause RJ, Pritchard CC, Shendure J et al (2016) Classification and characterization of microsatellite instability across 18 cancer types. Nat Med 22:1342–1350CrossRefGoogle Scholar
  39. 39.
    Ichikawa H, Nagahashi M, Shimada Y et al (2017) Actionable gene-based classification toward precision medicine in gastric cancer. Genome Med 9:93CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Hoelder S, Clarke PA, Workman P (2012) Discovery of small molecule cancer drugs: successes, challenges and opportunities. Mol Oncol 6:155–176CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Ledford H (2010) Big science: the cancer genome challenge. Nature 464:972–974CrossRefPubMedGoogle Scholar
  42. 42.
    Chang F, Li MM (2013) Clinical application of amplicon-based next-generation sequencing in cancer. Cancer Genet 206:413–419CrossRefPubMedGoogle Scholar
  43. 43.
    Van Allen EM, Wagle N, Levy MA (2013) Clinical analysis and interpretation of cancer genome data. J Clin Oncol 31:1825–1833CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Hampel H, Bennett RL, Buchanan A, Pearlman R et al (2015) A practice guideline from the American College of Medical Genetics and Genomics and the National Society of Genetic Counselors: referral indications for cancer predisposition assessment. Genet Med 17:70–87CrossRefPubMedGoogle Scholar
  45. 45.
    Desmedt C, Voet T, Sotiriou C et al (2012) Next-generation sequencing in breast cancer: first take home messages. Curr Opin Oncol 24:597–604CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    LeBlanc VG, Marra MA (2015) Next-generation sequencing approaches in cancer: where have they brought us and where will they take us? Cancers (Basel) 7:1925–1958CrossRefGoogle Scholar
  47. 47.
    Giuliano AE, Connolly JL, Edge SB et al (2017) Breast cancer-major changes in the American Joint Committee on Cancer eighth edition cancer staging manual. CA Cancer J Clin 67:290–303CrossRefPubMedGoogle Scholar
  48. 48.
    Buchtel KM, Vogel Postula KJ, Weiss S et al (2018) FDA approval of PARP inhibitors and the impact on genetic counseling and genetic testing practices. J Genet Couns 27:131–139CrossRefPubMedGoogle Scholar
  49. 49.
    Imai S, Ichikawa T, Sugiyama C et al (2018) Contribution of Human Liver and Intestinal Carboxylesterases to the Hydrolysis of Selexipag In Vitro. J Pharm Sci.  https://doi.org/10.1016/j.xphs.2018.09.022 CrossRefPubMedGoogle Scholar
  50. 50.
    Moreira RB, Alessandretti MB, Abrahao CM et al (2015) Next-generation sequencing (NGS) in metastatic gastrointestinal cancer (mGIC) patients: translation from sequence data into clinical practice. J Clin Oncol 33:72–72CrossRefGoogle Scholar
  51. 51.
    Lerner-Ellis J, Khalouei S, Sopik V (2015) Genetic risk assessment and prevention: the role of genetic testing panels in breast cancer. Expert Rev Anticancer Ther 15:1315–1326CrossRefPubMedGoogle Scholar
  52. 52.
    Hyman DM, Piha-Paul SA, Won H et al (2018) HER kinase inhibition in patients with HER2- and HER3-mutant cancers. Nature 554:189–194CrossRefPubMedPubMedCentralGoogle Scholar
  53. 53.
    Lowes LE, Bratman SV, Dittamore R et al (2016) Circulating Tumor Cells (CTC) and Cell-Free DNA (cfDNA) Workshop 2016: Scientific Opportunities and Logistics for Cancer Clinical Trial Incorporation. Int J Mol Sci.  https://doi.org/10.3390/ijms17091505 CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Shimomura A, Shiino S, Kawauchi J et al (2016) Novel combination of serum microRNA for detecting breast cancer in the early stage. Cancer Sci 107:326–334CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Japan Society of Clinical Oncology 2018

Authors and Affiliations

  • Toshifumi Wakai
    • 1
  • Pankaj Prasoon
    • 1
  • Yuki Hirose
    • 1
  • Yoshifumi Shimada
    • 1
  • Hiroshi Ichikawa
    • 1
  • Masayuki Nagahashi
    • 1
  1. 1.Division of Digestive and General SurgeryNiigata University Graduate School of Medical and Dental SciencesNiigataJapan

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